CKA Troubleshooting Practice Question
A Deployment named 'web' is failing to schedule pods. You run 'kubectl describe pod web-xyz' and see the event: '0/3 nodes are available: 3 Insufficient cpu.' What is the most likely cause?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The CPU request in the pod spec is too high
The error indicates that CPU requests are too high for the available node resources. Reducing CPU requests or adding more nodes can fix it.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
The CPU request in the pod spec is too high
Why this is correct
The scheduler evaluates the pod's CPU request against the allocatable CPU on each node after reserving resources for existing pods and system components. If the requested CPU exceeds what any node can accommodate, the scheduler reports 'Insufficient cpu' and leaves the pod Pending. This is a resource-fit failure, not an API or runtime error, so checking the pod's resources.requests is the first diagnostic.
- ✗
The network plugin is misconfigured
Why it's wrong here
A misconfigured network plugin, such as a broken CNI daemon or missing kube-proxy rules, would typically result in pods being scheduled but stuck in ContainerCreating or CrashLoopBackOff, or in connectivity failures. It would not produce an 'Insufficient cpu' scheduling error, because network plugins are not involved in the scheduler's resource feasibility checks. The scheduler only filters nodes for taints, affinity, and resource requests, not network readiness.
- ✗
The nodes have insufficient memory
Why it's wrong here
Memory pressure causes a distinct scheduling condition: the scheduler reports 'Insufficient memory' (or node pressure evictions) when sum of memory requests exceeds allocatable memory. If the error message explicitly says 'insufficient cpu', the constraint being violated is CPU, and adding memory or reducing memory allocations will not resolve the fit problem — the pod's CPU request must be reduced or the cluster must scale CPU capacity.
- ✗
The kubelet is not running on the nodes
Why it's wrong here
If the kubelet were not running on a node, the node's status would shift to NotReady and the scheduler would exclude it from placement decisions. However, 'Insufficient cpu' is a resource-fit condition computed by the kube-scheduler using Node.Status.Allocatable, and it can occur on fully Ready nodes simply because no node has enough unreserved CPU. The kubelet's liveness affects node readiness, not the scheduler's resource accounting.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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